Wearable Technologies and Artificial Intelligence for Personalised Health Monitoring

Pat Hanrahan

Wearable Technologies and Artificial Intelligence for Personalised Health Monitoring

Author(s)	Pat Hanrahan
Country	United States
Abstract	The rapid advancement of wearable technologies and Artificial Intelligence (AI) has transformed personalised healthcare by enabling continuous, real-time monitoring of physiological parameters, early disease detection, predictive health analytics, and personalised clinical interventions. Wearable devices—including smartwatches, fitness trackers, biosensors, smart clothing, electrocardiogram (ECG) monitors, and continuous glucose monitoring (CGM) systems—collect large volumes of health data that can be analysed using AI algorithms to support preventive, predictive, and precision medicine. These intelligent systems empower individuals to actively manage their health while assisting healthcare professionals in making timely, evidence-based clinical decisions. This study presents a comprehensive analysis of wearable technologies and Artificial Intelligence for personalised health monitoring. A qualitative analytical research methodology based on secondary data is employed to examine AI-driven wearable healthcare systems, machine learning algorithms, Internet of Medical Things (IoMT), cloud-based health platforms, digital twins, and remote patient monitoring technologies. The study evaluates how AI enhances physiological signal analysis, disease prediction, personalised treatment recommendations, behavioural monitoring, and healthcare accessibility. The findings indicate that AI-integrated wearable technologies significantly improve health monitoring accuracy, patient engagement, early diagnosis, chronic disease management, and clinical decision support. Deep learning algorithms enable automated analysis of ECG signals, heart rate variability, physical activity, sleep quality, blood oxygen saturation, blood pressure trends, glucose levels, and stress indicators. Furthermore, wearable health ecosystems facilitate remote healthcare delivery, telemedicine, and population health management through secure cloud infrastructures and intelligent analytics. Despite these advantages, challenges remain regarding data privacy, cybersecurity, interoperability, battery limitations, sensor accuracy, algorithm transparency, regulatory compliance, and ethical use of personal health data. Future research should investigate explainable AI, federated learning, digital twins for personalised medicine, multimodal biosensor integration, and privacy-preserving health analytics. The study concludes that wearable technologies combined with Artificial Intelligence represent a transformative approach to personalised healthcare by supporting continuous health monitoring, preventive medicine, intelligent clinical decision-making, and patient-centred healthcare delivery.
Keywords	Wearable Technology, Artificial Intelligence, Personalised Healthcare, Health Monitoring, Internet of Medical Things, Machine Learning, Digital Health, Remote Patient Monitoring, Precision Medicine.
Field	Engineering
Published In	Volume 1, Issue 6, November-December 2019
Published On	2019-11-13

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American Journal of Advanced Multidisciplinary Research and Innovation

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Wearable Technologies and Artificial Intelligence for Personalised Health Monitoring

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